composite measures of executive function and memory: …...backwards, wais-r digit symbol...
TRANSCRIPT
Rev Oct 23 2015
Composite measures of executive function and memory:
ADNI_EF and ADNI_Mem.
Laura E. Gibbons, PhD1, Adam C. Carle, PhD
2, R. Scott Mackin, PhD
3, Danielle
Harvey, PhD4, Shubhabrata Mukherjee, PhD
1, Philip Insel, MS
3, S. McKay Curtis,
PhD1, Alden Gross, PhD, MHS
5, Richard N. Jones, ScD
5, Dan Mungas, PhD
6,
Michael Weiner, MD3, and Paul K. Crane, MD MPH
1, for the Alzheimer’s Disease
Neuroimaging Initiative*
1. University of Washington, Box 359780, Harborview Medical Center, 325 Ninth Avenue, Seattle, WA 98104,
USA
2. University of Cincinnati School of Medicine, Cincinnati Children's Hospital Medical Center, and University of
Cincinnati College of Arts and Sciences, 3333 Burnet Avenue, MLC 7014, Cincinnati, OH 45229, USA
3. Center for Imaging of Neurodegenerative Diseases (CIND), San Francisco VA Medical Center, 4150 Clement
Street, San Francisco, CA 94121, USA
4. Division of Biostatistics, Department of Public Health Sciences, University of California, One Shields Avenue,
Davis, CA 95616, USA.
5. Department of Psychiatry, Institute for Aging Research, Hebrew Senior Life, 1200 Center Street, Boston, MA
02131, USA
6. Department of Neurology, UC Davis Medical Center, 4860 Y Street, Sacramento, CA 95817, USA
Contents Page 1 ADNI-EF Page 3 ADNI-MEM
Summary
We derived composite scores for executive functioning (ADNI-EF) and memory (ADNI-MEM)
using data from the ADNI neuropsychological battery using item response theory (IRT)
methods. The formation of ADNI-MEM was complicated by the use of different word lists in
the Rey Auditory Verbal Learning Test (RAVLT) and the ADAS-Cog, and by Logical Memory I
data missing by design. ADNI-EF and ADNI-MEM have been validated in published papers1,2
.
The methods below are adapted from those papers and updated to include issues with ADNI 2
and ADNI GO.
Method
ADNI-EF We used baseline data to develop ADNI-EF. Several of the authors (PKC, AC, and DM)
reviewed the neuropsychological battery to identify items which could be considered indicators
of EF. We refined our item selection using an iterative process in which we constructed a model
using confirmatory factor analysis, reviewed findings as a small group, and then constructed a
revised model. Our criteria for model fit were the confirmatory fit index (CFI), the Tucker Lewis
Index (TLI) and the root mean squared error of approximation (RMSEA), where criteria for
excellent fit include CFI>0.95, TLI >0.95, and RMSEA<0.05 3. We used Mplus (version 5)
4
with the theta parameterization and the WLSMV estimator. The final model for ADNI-EF
included Category Fluency—animals, Category Fluency—vegetables, Trails A and B, Digit span
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backwards, WAIS-R Digit Symbol Substitution, and 5 Clock Drawing items (circle, symbol,
numbers, hands, time).
These EF indicators utilized a variety of response formats that present challenges for
constructing summary or composite measures. The formats include counts in a pre-specified time
span (Category Fluency, WAIS-R Digit Symbol), times to completion (Trails), number of items
completed correctly (Digit Span Backwards), and dichotomous correct/incorrect (clock drawing).
We developed ordered categorical transformations of the raw data to facilitate development of
composite scores that did not make strong assumptions about the distributions of scores. We
recoded the raw scores into ordinal scales with as many as 10 categories, the maximum allowed
by Mplus for ordinal variables. Our categorical transformations were based on the empirically
observed distributions of the raw data, with a goal of maintaining variability in the tails at the
expense of maintaining variability in the middle of the distributions. Specifics on how Category
Fluency, WAIS-R Digit Symbol, Digit Span Backwards and Trails A and B were transformed
are given in Table 1.
Table 1. Recoding of scores with more than 10 categories for ADNI-EF.
Categorization
Original EF Score 0 1 2 3 4 5 6 7 8 9
Category Fluency—
Animals
0–5 6–7 8–9 10–12 13–16 17–20 21–23 24 25–27 28–60
Category Fluency—
Vegetables
0–3 4–5 6 7–8 9–11 12–14 15–17 18 19–20 21–31
WAIS-R Digit
Symbol
0–9 10–15 16–19 20–29 30–38 39–46 47–53 54–56 57–61 62–87
Digit Span
Backwards
1–2 3 4 5 6 7 8 9 10 11–12
Trails A
118–
150
94–
117
73–93 53–72 40–52 32–39 27–31 24–26 21–23 5–20
Trails B
261–
300
226–
260
196–
225
137–
195
96–
136
73–95 60–72 54–59 49–53 10–48
Bi-factor confirmatory factor analysis models5 played an important role in ADNI-EF
development. In this case, the single factor model was not a good representation of the data.
Specifically, as shown in Figure 1, a bi-factor structure that included secondary domain structure
for correlations between Category Fluency items and that included a methods factor for the
Clock Drawing items produced much improved measures of model fit. We considered additional
secondary structure, such as a residual correlation for the Trails tasks or for the two tests
involving digits, but these residual correlations had a negligible impact on model fit and did not
influence the loadings of other indicators on the primary factor. These considerations resulted in
our final confirmatory factor analysis bi-factor model, shown in Figure 1. Model fit was
excellent. The CFI was 0.99, the TLI was 0.99, and the RMSEA was 0.049.
Rev Oct 23 2015
We defined the metric for ADNI-EF to
have a mean of 0, and standard deviation
of 1, based on the 800 participants with
complete EF data at baseline. We used
item parameters (loadings and thresholds)
from the baseline model to compute
scores at each follow-up visit. The
resulting ADNI-EF scores are available
in the ADNI UWNPSYCHSUM file.
Final Mplus code to generate the scores is
in Appendix 1.
ADNI 2 and ADNI GO did not administer Category Fluency - Vegetables, Digit Span
Backwards, or WAIS-R Digit Symbol. An advantage of IRT scoring is that we can still compute
EF scores in ADNI 2 and ADNI GO using the other eight items and their item parameters. The
measurement error will be larger because of the missing items, but the scores are still valid and
on the same metric as scores based on all the items. This means that scores from the three phases
are directly comparable. By the same token, if anyone was missing an item at random, we still
were able to calculate a score.
ADNI-MEM
The memory items were also selected based on theory, and analyzed in Mplus, with recoded
variables (Table 2).
Table 2 ADNI-Mem items and their recoding. Categorization
Original Memory Score 0 1 2 3 4 5 6 7 8 9
RAVLT
Trial 1 0/2 3 4 5 6 7 8 9 10 11/15
Trial 2 0/2 3 4 5 6 7 8 9 10 11/15
Trial 3 0/2 3 4 5/6 7/8 9 10 11 12 13/14
Trial 4 0/3 4 5/6 7/8 9 10 11 12 13 14/15
Trial 5 0/3 4 5 6/7 8/9 10/11 12 13 14 15
Interference 0/1 2 3 4 5 6 7 8/15
Immediate recall 0 1/2 3/4 5/6 7 8 9 10/11 12/13 14/15
30 minute delay 0 1/2 3/4 5/6 7 8 9 10/11 12/13 14/15
Recognition 0 1 2/3 4/5 6/7 8/9 10/11 12/13 14 15
ADAS-Cog
Trial 1 0/1 2 3 4 5 6 7 8/10
Figure 1. Bifactor model for ADNI-EF
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Trial 2 0/2 3 4 5 6 7 8 9 10
Trial 3 0/2 3 4 5 6 7 8 9 10
Recall 0 1 2 3 4 5 6 7 8 9/10
Recognition present 0/3 4 5 6 7 8 9 10 11 12
Recognition absent 0/4 5/6 7 8 9 10 11 12
Logical Memory*
Immediate 0/1 2/3 4/5 6/7 8/9 10/12 13/14 15/16 17/18 19/25
Delay 0 1/2 3/4 5/8 9/11 12 13 14/15 16/17 18/25
MMSE*
Ball recall 2 1
Flag recall 2 1
Tree recall 2 1
*Values from the screening visit were used as baseline scores.
The task of modeling the memory data was complicated by the three forms of the ADAS-Cog
word lists and the two forms of the RAVLT word lists. It was not clear if these word lists were
equivalent; indeed past experience suggested that the RAVLT lists may be problematic.
Furthermore, Logical Memory was only assessed at annual visits. The only indicators
consistently present across visits were the three word recall items from the MMSE. Technically
these three dichotomous indicators could be used to anchor the scales across time points6, but we
were concerned that this anchoring would be too sparse for valid conclusions to be drawn.
Longitudinal bi-factor models incorporating the different versions of the tests and the missing
Logical Memory scores were also theoretically possible, but in practice proved impossible to fit
with these items in the ADNI data set. Therefore we investigated whether a single factor model
would be appropriate for the longitudinal data. Full details will be available in the published
paper, but here is a brief summary. Using the baseline data, a bi-factor model that accounted for
methods effects had superior fit compared to a single factor model, and to bi-factor models using
content-based subdomains. But based on a comparison of loadings on the overall memory factor
and the correlation between the single and bi-factor scores (0.99), we decided it was acceptable
to use a single factor model.
Next we divided the data set into two parts: first, the annual visits with data from all participants
(baseline, month 12, and month 24), and second, the other visits (month 6, 18, and 36; the month
36 visit had structurally missing data from people in the AD group). Logical Memory was
assessed at each of the visits in the first half of the data set, so those much richer indicators were
used as anchors alongside the three dichotomous MMSE indicators. Furthermore, at each of
those visits, only the first version of the RAVLT was assessed, so it could also act as an anchor.
The only thing that varied at those visits was thus the three different versions of the ADAS-Cog.
We fit a longitudinal model using all available data for the annual visits of the first half of the
data set. We identified the scale by specifying the variance of the general factor to be 1 at the
baseline visit, when its mean was 0. We allowed the mean and the variance of the general factor
to vary at other time points, and the general factors were freely correlated with each other. We
freely estimated the loadings on the general factor, but constrained those loadings from the same
indicators to be the same across time points. For example, for the first MMSE item, we freely
estimated the loading on the overall memory factor at each time point, but constrained that
loading to be the same at baseline, month 12, and month 24.
Rev Oct 23 2015
We captured point estimates for the loadings and thresholds for the three MMSE items, Logical
Memory I and II, and the three versions of the ADAS-Cog from the first half of the data set. We
then turned our attention to the second half of the data set that included data from study visits at
months 6, 18, and 36. The second version of the RAVLT word list was used at each of these
study visits. We used the MMSE items, the ADAS-Cog version 2 (month 6), version 1 (month
18), and version 3 (month 36), and Logical Memory (month 36) as anchors to estimate item
parameters for the second version of the RAVLT. The longitudinal modeling strategy was
similar to that described for the first half of the data. Because we were fixing item loadings and
thresholds for the anchor items, the scale was still anchored to the mean of 0 and variance of 1 at
the baseline visit. We freely estimated the means and variances at each of the study visits
included in this second half of the data. Script files for the developmental analyses are available
from the authors. Final code to estimate the memory scores is in Appendix 2. We extracted the
ADNI-MEM factor scores for each participant at each study visit. These analyses were based on
data collected through the 36-month visit. The 48-month neuropsych battery had the same
memory items in the same versions as the baseline data, so baseline parameters were used to
compute 48-month scores. The ADNI-MEM scores are available in the UWNPSYCHSUM file.
Version effects for the RAVLT and the ADAS-Cog.
The loadings for each of the indicators from the two versions of the RAVLT were very similar;
as a proportion, they ranged from 5% smaller to 3% larger between the two versions. The
difficulty levels for the category thresholds, however, displayed important differences between
the two versions, as shown in the plot of the item thresholds in Figure 2. For all of the trials with
the exception of List B (the distractor list), the Version B list is more difficult (has higher
thresholds) than the Version A list.
Fig. 2 Difficulty levels for the elements of the two versions of the RAVLT. The five learning trials are indicated by
the numbers 1 through 5; the interference trial by the letter B, the first recall trial by the number 6; delayed recall by
“Recall”, and the recognition task by “Recognition”. Version A difficulty thresholds are denoted with blue circles,
while version B difficulty thresholds are denoted with green diamonds. In this plot, the difficulty levels are plotted
on the y axis in z-statistic units; higher numbers indicate higher memory ability / higher item difficulty. Considering
the two versions of learning trial 1, version A is easier for each threshold. At an overall memory ability level of -0.5,
for example, higher proportions of people will be above the first threshold for version A, and lower proportions of
people above that same threshold for version B. At every threshold the green diamonds are higher than the blue dots.
For the second through 5th
learning trials, this difference is dramatic at the top end, as the top threshold on version A
is only as difficult as the 2nd
to highest threshold on version B.
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The ADAS-Cog versions were more similar to each other, at least in terms of category thresholds
(see Figure 3). Version 1 had a greater spread of thresholds than Version 2 and to a lesser extent
than Version 3, which means that it should be somewhat better able to differentiate among
people at the extremes of memory ability with fewer ceiling or floor scores. The loadings for the
learning trials and recall of the three versions of the ADAS-Cog list learning task were very
similar to each other, with differences ranging from 4 percent lower to 2 percent higher. The
recognition present and recognition absent tasks had somewhat dissimilar loadings. In no case
were these strong indicators of overall memory (standardized loadings ranged from 0.43 to 0.56,
roughly half the magnitude of loadings for the list learning indicators). The largest overall
difference in loading between versions was 0.13 for recognition correct between Version A and
Version C, which in terms of percentage was a 30% difference in loadings.
Fig. 3 Loadings for the memory items from the three versions of the ADAS-Cog. Recog = Recognition. Version 1
threshold difficulty levels are depicted with blue circles, Version 2 with green diamonds, and Version 3 with red
triangles. In this plot, the difficulty levels are plotted on the y axis in z-statistic units; higher numbers indicate higher
memory ability / higher item difficulty Version 1 has greater spread than Version 2 and to a lesser extent than
version 3, meaning it will have slightly smaller ceiling and floor effects. Unlike the RAVLT, no version appears to
be consistently easier or harder than the other versions.
-2
-1
0
1
2
3
Dif
ficu
lty level
1
1
2 3 4 5 B 6 Recall Recognition
Rev Oct 23 2015
Spanish Language
A few participants in ADNI2/GO are being tested in Spanish. We have computed their scores
using the item parameters derived in English tests. So far there are too few Spanish test-takers to
evaluate whether this is appropriate. If you want to omit their scores, look for even-numbered
values of the variable "WORDLIST" in the adas_adnigo2 file.
References
1. Gibbons LE, Carle AC, Mackin RS, et al. A composite score for executive functioning,
validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with
baseline mild cognitive impairment. Brain Imaging Behav. 2012.
2. Crane PK, Carle A, Gibbons LE, et al. Development and assessment of a composite score
for memory in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Brain Imaging
Behav. 2012.
3. Reeve BB, Hays RD, Bjorner JB, et al. Psychometric evaluation and calibration of
health-related quality of life item banks: plans for the Patient-Reported Outcomes
Measurement Information System (PROMIS). Med Care. 2007;45(5 Suppl 1):S22-31.
4. Mplus: statistical analysis with latent variables [computer program]. Version 5.1. Los
Angeles, CA: Muthén & Muthén; 1998-2007.
-2
-1
0
1
2
3
Dif
fic
ult
y l
ev
el
Trial 1 Trial 2 Trial 3 Recall Recog
PresentRecog
Absent
Rev Oct 23 2015
5. McDonald RP. Test theory: a unified treatment. Mahwah, N.J.: Lawrence Erlbaum; 1999.
6. Reise SP, Widaman KF, Pugh RH. Confirmatory factor analysis and item response
theory: Two approaches for exploring measurement invariance. Psychological Bulletin.
1993;114(3):552-566.
About the Authors
This document was prepared by Laura Gibbons at the University of Washington. For more
information or to ask for updated files, please contact Laura Gibbons by email at
[email protected] or at 1-206-744-1842.
Notice: This document is presented by the author(s) as a service to ADNI data users. However, users should be
aware that no formal review process has vetted this document and that ADNI cannot guarantee the accuracy or
utility of this document.
Appendix 1. Mplus code for ADNI-EF
Note that the following ADNI variables were recoded as in Table 1.
EF item ADNI Name Recoded Name
Category Fluency—Animals catanimsc mecatat
Category Fluency—Vegetables catvegesc mecatvt
WAIS-R Digit Symbol digitscor medigit
Digit Span Backwards dspanbac medsbc
Trails A
traascor metatne
Trails B
trabscor metbtne
You’ll need to add lines to refer to your data file and the missing value codes.
VARIABLE:
NAMES = rid mecatat mecatvt medigit medsbc metatne metbtne clockcirc
clocksym clocknum clockhand clocktime ;
CATEGORICAL = mecatat-clocktime;
IDVARIABLE = rid;
ANALYSIS:
PARAMETERIZATION = theta;
OUTPUT:
STANDARDIZED;
SAVEDATA:
file is ef_scores_bifactor.txt; save=fscores;
MODEL:
adni_ef by mecatat @ 0.732 ;
adni_ef by mecatvt @ 0.755 ;
adni_ef by medsbc @ 0.599 ;
adni_ef by metatne @ 1.095 ;
adni_ef by metbtne @ 1.594 ;
adni_ef by medigit @ 1.627 ;
adni_ef by clockcirc @ 0.423 ;
adni_ef by clocksym @ 0.610 ;
adni_ef by clocknum @ 0.656 ;
adni_ef by clockhand @ 1.959 ;
adni_ef by clocktime @ 0.985 ;
clock by clockcirc @ 0.486 ;
Rev Oct 23 2015
clock by clocksym @ 0.413 ;
clock by clocknum @ 0.863 ;
clock by clockhand @ 2.040 ;
clock by clocktime @ 0.810 ;
adni_ef with clock @ 0.000 ;
mecatat with mecatvt @ 0.444 ;
adni_ef @ 1.000 ;
clock @ 1.000 ;
[mecatat$1 @ -2.456] ;
[mecatat$2 @ -1.980] ;
[mecatat$3 @ -1.488] ;
[mecatat$4 @ -0.816] ;
[mecatat$5 @ 0.097] ;
[mecatat$6 @ 0.947] ;
[mecatat$7 @ 1.545] ;
[mecatat$8 @ 1.795] ;
[mecatat$9 @ 2.331] ;
[mecatvt$1 @ -2.405] ;
[mecatvt$2 @ -1.782] ;
[mecatvt$3 @ -1.465] ;
[mecatvt$4 @ -0.763] ;
[mecatvt$5 @ 0.158] ;
[mecatvt$6 @ 1.027] ;
[mecatvt$7 @ 1.720] ;
[mecatvt$8 @ 1.975] ;
[mecatvt$9 @ 2.456] ;
[medsbc$1 @ -2.151] ;
[medsbc$2 @ -1.698] ;
[medsbc$3 @ -0.940] ;
[medsbc$4 @ -0.288] ;
[medsbc$5 @ 0.333] ;
[medsbc$6 @ 0.781] ;
[medsbc$7 @ 1.246] ;
[medsbc$8 @ 1.581] ;
[medsbc$9 @ 2.024] ;
[metatne$1 @ -2.663] ;
[metatne$2 @ -2.305] ;
[metatne$3 @ -1.839] ;
[metatne$4 @ -0.994] ;
[metatne$5 @ -0.028] ;
[metatne$6 @ 0.914] ;
[metatne$7 @ 1.733] ;
[metatne$8 @ 2.370] ;
[metatne$9 @ 2.875] ;
[metbtne$1 @ -2.033] ;
[metbtne$2 @ -1.814] ;
[metbtne$3 @ -1.558] ;
[metbtne$4 @ -0.782] ;
[metbtne$5 @ 0.260] ;
[metbtne$6 @ 1.437] ;
[metbtne$7 @ 2.494] ;
[metbtne$8 @ 3.007] ;
[metbtne$9 @ 3.610] ;
[medigit$1 @ -3.921] ;
[medigit$2 @ -3.141] ;
[medigit$3 @ -2.489] ;
[medigit$4 @ -1.228] ;
[medigit$5 @ 0.090] ;
[medigit$6 @ 1.419] ;
[medigit$7 @ 2.461] ;
[medigit$8 @ 2.910] ;
Rev Oct 23 2015
[medigit$9 @ 3.703] ;
[clockcirc$1 @ -2.581] ;
[clocksym$1 @ -0.733] ;
[clocknum$1 @ -1.602] ;
[clockhand$1 @ -4.513] ;
[clocktime$1 @ -0.663] ;
Appendix 2. Stata and Mplus code for ADNI-Mem.
We used the Stata program –runmplus-, which is a free user-written download available by
typing “ssc install runmplus” in Stata. You must also have Mplus on your computer for this to
work.
The memory items were recoded as in Table 2.
Memory item ADNI Name Recoded Name
RAVLT
Trial 1 avtot1 mmra1
Trial 2 avtot2 mmra2
Trial 3 avtot3 mmra3
Trial 4 avtot4 mmra4
Trial 5 avtot5 mmra5
Interference avtotb mmrab
Immediate recall avtot6 mmra6
30 minute delay avdel30min mmradrc
Recognition avdeltot mmrarc
ADAS-Cog
Trial 1 cot1sco mmadlt1
Trial 2 cot2sco mmadlt2
Trial 3 cot3sco mmadlt3
Recall cot4tot mmadd
Recognition present * mmadrg1
Recognition absent * mmadrg2
Logical Memory*
Immediate limmtotal mmlmrc
Delay ldeltotal mmlmd
MMSE*
Ball recall balldl mmballdl
Flag recall flagdl mmflagdl
Tree recall treedl mmtreedl
* see code below.
Stata code to create the ADAS recognition items egen adrg1=rowtotal(co8magaz co8wizrd co8van co8leprd co8sea co8train ///
co8coin co8inst co8board co8anchr co8gem co8fund) if inlist(visnum,0,18,48)
tempvar a6 a12 b6 b12
egen `a6'= rowtotal(co8nurse co8wizrd co8leprd co8sea co8ship co8map ///
co8milk co8vol co8forst co8fund co8edge co8cake) if visnum==6 | visnum==24
replace adrg1=`a6' if visnum==6 | visnum==24
egen `a12'=rowtotal(co8nurse co8wizrd co8sale co8sea co8train co8map ///
co8axe co8milk co8vol co8gem co8cat co8edge) if visnum==12 | visnum==36
replace adrg1=`a12' if visnum==12 | visnum==36
Rev Oct 23 2015
replace adrg1=. if missing(co8magaz, co8wizrd,co8van, co8leprd, co8sea, co8train, ///
co8coin, co8inst, co8board, co8anchr, co8gem, co8fund)
la var adrg1 "ADAS-cog correctly identified as seen"
egen adrg2=rowtotal(co8nurse co8sale co8ship co8map co8axe co8carrt ///
co8milk co8vol co8forst co8cat co8edge co8cake) if inlist(visnum,0,18,48)
egen `b6'=rowtotal(co8magaz co8van co8sale co8train co8coin co8inst ///
co8axe co8board co8carrt co8anchr co8gem co8cat) if visnum==6 | visnum==24
replace adrg2=`b6' if visnum==6 | visnum==24
egen `b12'=rowtotal(co8magaz co8van co8leprd co8coin co8ship co8inst ///
co8board co8carrt co8forst co8anchr co8fund co8cake) if visnum==12 | visnum==36
replace adrg2=`b12' if visnum==12 | visnum==36
replace adrg2=12-adrg2
replace adrg2=. if missing(co8nurse, co8sale, co8ship, co8map, co8axe, co8carrt, ///
co8milk, co8vol, co8forst, co8cat, co8edge, co8cake)
la var adrg2 "ADAS-cog correctly identified as not seen"
Stata and Mplus code (runmplus) to generate ADNI-Mem
This is based on having the recoded items in a data set called ADNI_Mem.dta
* a bit unwieldy, but it’s safest to give you what was actually done.
use ADNI_Mem, clear
keep mm* rid visnum
* how he did it
rename mmlmrc lmrc
rename mmlmd lmd
rename mmradrc radrc
rename mmrarc rarc
rename mmra6 ra6
rename mmadrg1 adrg1
rename mmadrg2 adrg2
rename mmadlt1 adlt1
rename mmadlt2 adlt2
rename mmadlt3 adlt3
rename mmadd add
rename mmra1 ra1
rename mmra2 ra2
rename mmra3 ra3
rename mmra4 ra4
rename mmra5 ra5
rename mmrab rab
rename mmballdl balldl
rename mmflagdl flagdl
rename mmtreedl treedl
#d ;
local vlist "lmrc lmd radrc
ra6 adrg1 adrg2
adlt1 adlt2 adlt3
add ra1 ra2
ra3 ra4 ra5
rab balldl flagdl
treedl rarc" ;
#d cr
reshape wide `vlist', i(rid) j(visnum)
notes:from ADNI_Mem
save "memory_wide", replace
******************************************************************
Rev Oct 23 2015
* baseline
******************************************************************
#d ;
local vlist lmrc0 lmd0 radrc0 rarc0 ra60 adrg10 adrg20 adlt10 adlt20
adlt30 add0 ra10 ra20 ra30 ra40 ra50 rab0 balldl0 flagdl0 treedl0;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
MEM0 BY LMRC0 @ 0.837 ; ///
MEM0 BY LMD0 @ 0.846 ; ///
MEM0 BY RADRC0 @ 0.876 ; ///
MEM0 BY RARC0 @ 0.728 ; ///
MEM0 BY RA60 @ 0.85 ; ///
MEM0 BY ADRG10 @ 0.43 ; ///
MEM0 BY ADRG20 @ 0.507 ; ///
MEM0 BY ADLT10 @ 0.792 ; ///
MEM0 BY ADLT20 @ 0.858 ; ///
MEM0 BY ADLT30 @ 0.844 ; ///
MEM0 BY ADD0 @ 0.898 ; ///
MEM0 BY RA10 @ 0.661 ; ///
MEM0 BY RA20 @ 0.807 ; ///
MEM0 BY RA30 @ 0.852 ; ///
MEM0 BY RA40 @ 0.884 ; ///
MEM0 BY RA50 @ 0.882 ; ///
MEM0 BY RAB0 @ 0.615 ; ///
MEM0 BY BALLDL0 @ 0.748 ; ///
MEM0 BY FLAGDL0 @ 0.777 ; ///
MEM0 BY TREEDL0 @ 0.751 ; ///
[ LMRC0$1 @ -1.369 ] ; ///
[ LMRC0$2 @ -0.841 ] ; ///
[ LMRC0$3 @ -0.412 ] ; ///
[ LMRC0$4 @ -0.079 ] ; ///
[ LMRC0$5 @ 0.225 ] ; ///
[ LMRC0$6 @ 0.638 ] ; ///
[ LMRC0$7 @ 0.946 ] ; ///
[ LMRC0$8 @ 1.296 ] ; ///
[ LMRC0$9 @ 1.702 ] ; ///
[ LMD0$1 @ -0.637 ] ; ///
[ LMD0$2 @ -0.289 ] ; ///
[ LMD0$3 @ 0.006 ] ; ///
[ LMD0$4 @ 0.458 ] ; ///
[ LMD0$5 @ 0.74 ] ; ///
[ LMD0$6 @ 0.854 ] ; ///
[ LMD0$7 @ 0.972 ] ; ///
[ LMD0$8 @ 1.267 ] ; ///
[ LMD0$9 @ 1.676 ] ; ///
[ RADRC0$1 @ -0.248 ] ; ///
[ RADRC0$2 @ 0.109 ] ; ///
[ RADRC0$3 @ 0.368 ] ; ///
[ RADRC0$4 @ 0.668 ] ; ///
[ RADRC0$5 @ 0.807 ] ; ///
[ RADRC0$6 @ 0.97 ] ; ///
[ RADRC0$7 @ 1.126 ] ; ///
[ RADRC0$8 @ 1.453 ] ; ///
[ RADRC0$9 @ 1.891 ] ; ///
[ RARC0$1 @ -1.624 ] ; ///
[ RARC0$2 @ -1.519 ] ; ///
[ RARC0$3 @ -1.253 ] ; ///
[ RARC0$4 @ -0.88 ] ; ///
[ RARC0$5 @ -0.543 ] ; ///
[ RARC0$6 @ -0.215 ] ; ///
Rev Oct 23 2015
[ RARC0$7 @ 0.166 ] ; ///
[ RARC0$8 @ 0.644 ] ; ///
[ RARC0$9 @ 1.053 ] ; ///
[ RA60$1 @ -0.824 ] ; ///
[ RA60$2 @ -0.242 ] ; ///
[ RA60$3 @ 0.203 ] ; ///
[ RA60$4 @ 0.526 ] ; ///
[ RA60$5 @ 0.668 ] ; ///
[ RA60$6 @ 0.859 ] ; ///
[ RA60$7 @ 1.036 ] ; ///
[ RA60$8 @ 1.424 ] ; ///
[ RA60$9 @ 1.835 ] ; ///
[ ADRG10$1 @ -1.949 ] ; ///
[ ADRG10$2 @ -1.632 ] ; ///
[ ADRG10$3 @ -1.392 ] ; ///
[ ADRG10$4 @ -1.111 ] ; ///
[ ADRG10$5 @ -0.844 ] ; ///
[ ADRG10$6 @ -0.436 ] ; ///
[ ADRG10$7 @ -0.04 ] ; ///
[ ADRG10$8 @ 0.453 ] ; ///
[ ADRG10$9 @ 1.009 ] ; ///
[ ADRG20$1 @ -1.791 ] ; ///
[ ADRG20$2 @ -1.393 ] ; ///
[ ADRG20$3 @ -1.234 ] ; ///
[ ADRG20$4 @ -0.995 ] ; ///
[ ADRG20$5 @ -0.72 ] ; ///
[ ADRG20$6 @ -0.335 ] ; ///
[ ADRG20$7 @ 0.189 ] ; ///
[ ADLT10$1 @ -1.507 ] ; ///
[ ADLT10$2 @ -0.872 ] ; ///
[ ADLT10$3 @ -0.371 ] ; ///
[ ADLT10$4 @ 0.177 ] ; ///
[ ADLT10$5 @ 0.693 ] ; ///
[ ADLT10$6 @ 1.346 ] ; ///
[ ADLT10$7 @ 1.791 ] ; ///
[ ADLT20$1 @ -1.61 ] ; ///
[ ADLT20$2 @ -1.208 ] ; ///
[ ADLT20$3 @ -0.709 ] ; ///
[ ADLT20$4 @ -0.217 ] ; ///
[ ADLT20$5 @ 0.319 ] ; ///
[ ADLT20$6 @ 0.736 ] ; ///
[ ADLT20$7 @ 1.288 ] ; ///
[ ADLT20$8 @ 1.97 ] ; ///
[ ADLT30$1 @ -1.91 ] ; ///
[ ADLT30$2 @ -1.443 ] ; ///
[ ADLT30$3 @ -1.02 ] ; ///
[ ADLT30$4 @ -0.566 ] ; ///
[ ADLT30$5 @ -0.026 ] ; ///
[ ADLT30$6 @ 0.411 ] ; ///
[ ADLT30$7 @ 0.927 ] ; ///
[ ADLT30$8 @ 1.633 ] ; ///
[ ADD0$1 @ -1.147 ] ; ///
[ ADD0$2 @ -0.744 ] ; ///
[ ADD0$3 @ -0.444 ] ; ///
[ ADD0$4 @ -0.14 ] ; ///
[ ADD0$5 @ 0.115 ] ; ///
[ ADD0$6 @ 0.397 ] ; ///
[ ADD0$7 @ 0.674 ] ; ///
[ ADD0$8 @ 0.975 ] ; ///
[ ADD0$9 @ 1.461 ] ; ///
[ RA10$1 @ -1.609 ] ; ///
Rev Oct 23 2015
[ RA10$2 @ -1.049 ] ; ///
[ RA10$3 @ -0.413 ] ; ///
[ RA10$4 @ 0.225 ] ; ///
[ RA10$5 @ 0.795 ] ; ///
[ RA10$6 @ 1.319 ] ; ///
[ RA10$7 @ 1.776 ] ; ///
[ RA20$1 @ -1.46 ] ; ///
[ RA20$2 @ -0.966 ] ; ///
[ RA20$3 @ -0.505 ] ; ///
[ RA20$4 @ -0.034 ] ; ///
[ RA20$5 @ 0.401 ] ; ///
[ RA20$6 @ 0.769 ] ; ///
[ RA20$7 @ 1.137 ] ; ///
[ RA20$8 @ 1.436 ] ; ///
[ RA20$9 @ 1.713 ] ; ///
[ RA30$1 @ -1.567 ] ; ///
[ RA30$2 @ -1.172 ] ; ///
[ RA30$3 @ -0.755 ] ; ///
[ RA30$4 @ 0.048 ] ; ///
[ RA30$5 @ 0.677 ] ; ///
[ RA30$6 @ 0.917 ] ; ///
[ RA30$7 @ 1.195 ] ; ///
[ RA30$8 @ 1.439 ] ; ///
[ RA30$9 @ 1.67 ] ; ///
[ RA40$1 @ -1.261 ] ; ///
[ RA40$2 @ -0.84 ] ; ///
[ RA40$3 @ -0.122 ] ; ///
[ RA40$4 @ 0.42 ] ; ///
[ RA40$5 @ 0.649 ] ; ///
[ RA40$6 @ 0.884 ] ; ///
[ RA40$7 @ 1.124 ] ; ///
[ RA40$8 @ 1.339 ] ; ///
[ RA40$9 @ 1.663 ] ; ///
[ RA50$1 @ -1.348 ] ; ///
[ RA50$2 @ -0.94 ] ; ///
[ RA50$3 @ -0.541 ] ; ///
[ RA50$4 @ 0.045 ] ; ///
[ RA50$5 @ 0.472 ] ; ///
[ RA50$6 @ 0.912 ] ; ///
[ RA50$7 @ 1.149 ] ; ///
[ RA50$8 @ 1.402 ] ; ///
[ RA50$9 @ 1.746 ] ; ///
[ RAB0$1 @ -1.3 ] ; ///
[ RAB0$2 @ -0.675 ] ; ///
[ RAB0$3 @ -0.063 ] ; ///
[ RAB0$4 @ 0.549 ] ; ///
[ RAB0$5 @ 1.075 ] ; ///
[ RAB0$6 @ 1.508 ] ; ///
[ RAB0$7 @ 1.868 ] ; ///
[ BALLDL0$1 @ -0.509 ] ; ///
[ FLAGDL0$1 @ -0.033 ] ; ///
[ TREEDL0$1 @ -0.127 ] ; ///
) ///
savedata(save=fscores; file=mempkc111019_00.dat) ///
savelog(trash)
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
sort rid
tempfile f1
Rev Oct 23 2015
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem0
sort rid
capture save "mem0", replace
******************************************************************
* 48 month the same (but take out [adrg148$9])
******************************************************************
use "memory_wide", clear
#d ;
local vlist lmrc48 lmd48 radrc48 rarc48 ra648 adrg148 adrg248 adlt148 adlt248
adlt348 add48 ra148 ra248 ra348 ra448 ra548 rab48 balldl48 flagdl48 treedl48;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
mem48 BY LMRC48 @ 0.837 ; ///
mem48 BY LMD48 @ 0.846 ; ///
mem48 BY RADRC48 @ 0.876 ; ///
mem48 BY RARC48 @ 0.728 ; ///
mem48 BY RA648 @ 0.85 ; ///
mem48 BY ADRG148 @ 0.43 ; ///
mem48 BY ADRG248 @ 0.507 ; ///
mem48 BY ADLT148 @ 0.792 ; ///
mem48 BY ADLT248 @ 0.858 ; ///
mem48 BY ADLT348 @ 0.844 ; ///
mem48 BY ADD48 @ 0.898 ; ///
mem48 BY RA148 @ 0.661 ; ///
mem48 BY RA248 @ 0.807 ; ///
mem48 BY RA348 @ 0.852 ; ///
mem48 BY RA448 @ 0.884 ; ///
mem48 BY RA548 @ 0.882 ; ///
mem48 BY RAB48 @ 0.615 ; ///
mem48 BY BALLDL48 @ 0.748 ; ///
mem48 BY FLAGDL48 @ 0.777 ; ///
mem48 BY TREEDL48 @ 0.751 ; ///
[ LMRC48$1 @ -1.369 ] ; ///
[ LMRC48$2 @ -0.841 ] ; ///
[ LMRC48$3 @ -0.412 ] ; ///
[ LMRC48$4 @ -0.079 ] ; ///
[ LMRC48$5 @ 0.225 ] ; ///
[ LMRC48$6 @ 0.638 ] ; ///
[ LMRC48$7 @ 0.946 ] ; ///
[ LMRC48$8 @ 1.296 ] ; ///
[ LMRC48$9 @ 1.702 ] ; ///
[ LMD48$1 @ -0.637 ] ; ///
[ LMD48$2 @ -0.289 ] ; ///
[ LMD48$3 @ 0.006 ] ; ///
[ LMD48$4 @ 0.458 ] ; ///
[ LMD48$5 @ 0.74 ] ; ///
[ LMD48$6 @ 0.854 ] ; ///
[ LMD48$7 @ 0.972 ] ; ///
[ LMD48$8 @ 1.267 ] ; ///
[ LMD48$9 @ 1.676 ] ; ///
[ RADRC48$1 @ -0.248 ] ; ///
[ RADRC48$2 @ 0.109 ] ; ///
[ RADRC48$3 @ 0.368 ] ; ///
[ RADRC48$4 @ 0.668 ] ; ///
Rev Oct 23 2015
[ RADRC48$5 @ 0.807 ] ; ///
[ RADRC48$6 @ 0.97 ] ; ///
[ RADRC48$7 @ 1.126 ] ; ///
[ RADRC48$8 @ 1.453 ] ; ///
[ RADRC48$9 @ 1.891 ] ; ///
[ RARC48$1 @ -1.624 ] ; ///
[ RARC48$2 @ -1.519 ] ; ///
[ RARC48$3 @ -1.253 ] ; ///
[ RARC48$4 @ -0.88 ] ; ///
[ RARC48$5 @ -0.543 ] ; ///
[ RARC48$6 @ -0.215 ] ; ///
[ RARC48$7 @ 0.166 ] ; ///
[ RARC48$8 @ 0.644 ] ; ///
[ RARC48$9 @ 1.053 ] ; ///
[ RA648$1 @ -0.824 ] ; ///
[ RA648$2 @ -0.242 ] ; ///
[ RA648$3 @ 0.203 ] ; ///
[ RA648$4 @ 0.526 ] ; ///
[ RA648$5 @ 0.668 ] ; ///
[ RA648$6 @ 0.859 ] ; ///
[ RA648$7 @ 1.036 ] ; ///
[ RA648$8 @ 1.424 ] ; ///
[ RA648$9 @ 1.835 ] ; ///
[ ADRG148$1 @ -1.949 ] ; ///
[ ADRG148$2 @ -1.632 ] ; ///
[ ADRG148$3 @ -1.392 ] ; ///
[ ADRG148$4 @ -1.111 ] ; ///
[ ADRG148$5 @ -0.844 ] ; ///
[ ADRG148$6 @ -0.436 ] ; ///
[ ADRG148$7 @ -0.04 ] ; ///
[ ADRG148$8 @ 0.453 ] ; ///
[ ADRG248$1 @ -1.791 ] ; ///
[ ADRG248$2 @ -1.393 ] ; ///
[ ADRG248$3 @ -1.234 ] ; ///
[ ADRG248$4 @ -0.995 ] ; ///
[ ADRG248$5 @ -0.72 ] ; ///
[ ADRG248$6 @ -0.335 ] ; ///
[ ADRG248$7 @ 0.189 ] ; ///
[ ADLT148$1 @ -1.507 ] ; ///
[ ADLT148$2 @ -0.872 ] ; ///
[ ADLT148$3 @ -0.371 ] ; ///
[ ADLT148$4 @ 0.177 ] ; ///
[ ADLT148$5 @ 0.693 ] ; ///
[ ADLT148$6 @ 1.346 ] ; ///
[ ADLT148$7 @ 1.791 ] ; ///
[ ADLT248$1 @ -1.61 ] ; ///
[ ADLT248$2 @ -1.208 ] ; ///
[ ADLT248$3 @ -0.709 ] ; ///
[ ADLT248$4 @ -0.217 ] ; ///
[ ADLT248$5 @ 0.319 ] ; ///
[ ADLT248$6 @ 0.736 ] ; ///
[ ADLT248$7 @ 1.288 ] ; ///
[ ADLT248$8 @ 1.97 ] ; ///
[ ADLT348$1 @ -1.91 ] ; ///
[ ADLT348$2 @ -1.443 ] ; ///
[ ADLT348$3 @ -1.02 ] ; ///
[ ADLT348$4 @ -0.566 ] ; ///
[ ADLT348$5 @ -0.026 ] ; ///
[ ADLT348$6 @ 0.411 ] ; ///
[ ADLT348$7 @ 0.927 ] ; ///
[ ADLT348$8 @ 1.633 ] ; ///
Rev Oct 23 2015
[ ADD48$1 @ -1.147 ] ; ///
[ ADD48$2 @ -0.744 ] ; ///
[ ADD48$3 @ -0.444 ] ; ///
[ ADD48$4 @ -0.14 ] ; ///
[ ADD48$5 @ 0.115 ] ; ///
[ ADD48$6 @ 0.397 ] ; ///
[ ADD48$7 @ 0.674 ] ; ///
[ ADD48$8 @ 0.975 ] ; ///
[ ADD48$9 @ 1.461 ] ; ///
[ RA148$1 @ -1.609 ] ; ///
[ RA148$2 @ -1.049 ] ; ///
[ RA148$3 @ -0.413 ] ; ///
[ RA148$4 @ 0.225 ] ; ///
[ RA148$5 @ 0.795 ] ; ///
[ RA148$6 @ 1.319 ] ; ///
[ RA148$7 @ 1.776 ] ; ///
[ RA248$1 @ -1.46 ] ; ///
[ RA248$2 @ -0.966 ] ; ///
[ RA248$3 @ -0.505 ] ; ///
[ RA248$4 @ -0.034 ] ; ///
[ RA248$5 @ 0.401 ] ; ///
[ RA248$6 @ 0.769 ] ; ///
[ RA248$7 @ 1.137 ] ; ///
[ RA248$8 @ 1.436 ] ; ///
[ RA248$9 @ 1.713 ] ; ///
[ RA348$1 @ -1.567 ] ; ///
[ RA348$2 @ -1.172 ] ; ///
[ RA348$3 @ -0.755 ] ; ///
[ RA348$4 @ 0.048 ] ; ///
[ RA348$5 @ 0.677 ] ; ///
[ RA348$6 @ 0.917 ] ; ///
[ RA348$7 @ 1.195 ] ; ///
[ RA348$8 @ 1.439 ] ; ///
[ RA348$9 @ 1.67 ] ; ///
[ RA448$1 @ -1.261 ] ; ///
[ RA448$2 @ -0.84 ] ; ///
[ RA448$3 @ -0.122 ] ; ///
[ RA448$4 @ 0.42 ] ; ///
[ RA448$5 @ 0.649 ] ; ///
[ RA448$6 @ 0.884 ] ; ///
[ RA448$7 @ 1.124 ] ; ///
[ RA448$8 @ 1.339 ] ; ///
[ RA448$9 @ 1.663 ] ; ///
[ RA548$1 @ -1.348 ] ; ///
[ RA548$2 @ -0.94 ] ; ///
[ RA548$3 @ -0.541 ] ; ///
[ RA548$4 @ 0.045 ] ; ///
[ RA548$5 @ 0.472 ] ; ///
[ RA548$6 @ 0.912 ] ; ///
[ RA548$7 @ 1.149 ] ; ///
[ RA548$8 @ 1.402 ] ; ///
[ RA548$9 @ 1.746 ] ; ///
[ RAB48$1 @ -1.3 ] ; ///
[ RAB48$2 @ -0.675 ] ; ///
[ RAB48$3 @ -0.063 ] ; ///
[ RAB48$4 @ 0.549 ] ; ///
[ RAB48$5 @ 1.075 ] ; ///
[ RAB48$6 @ 1.508 ] ; ///
[ RAB48$7 @ 1.868 ] ; ///
[ BALLDL48$1 @ -0.509 ] ; ///
[ FLAGDL48$1 @ -0.033 ] ; ///
Rev Oct 23 2015
[ TREEDL48$1 @ -0.127 ] ; ///
) ///
savedata(save=fscores; file=mempkc111019_00.dat) ///
savelog(trash)
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
sort rid
tempfile f1
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem48
sort rid
capture save "mem48", replace
******************************************************************
* 6-month
******************************************************************
use "memory_wide", clear
#d ;
local vlist radrc6 rarc6 ra66 adrg16 adrg26 adlt16 adlt26 adlt36 add6
ra16 ra26 ra36 ra46 ra56 rab6 balldl6 flagdl6 treedl6;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
MEM6 BY RADRC6 @ 0.885 ; ///
MEM6 BY RARC6 @ 0.716 ; ///
MEM6 BY RA66 @ 0.862 ; ///
MEM6 BY ADRG16 @ 0.478 ; ///
MEM6 BY ADRG26 @ 0.533 ; ///
MEM6 BY ADLT16 @ 0.79 ; ///
MEM6 BY ADLT26 @ 0.828 ; ///
MEM6 BY ADLT36 @ 0.835 ; ///
MEM6 BY ADD6 @ 0.862 ; ///
MEM6 BY RA16 @ 0.649 ; ///
MEM6 BY RA26 @ 0.826 ; ///
MEM6 BY RA36 @ 0.876 ; ///
MEM6 BY RA46 @ 0.884 ; ///
MEM6 BY RA56 @ 0.877 ; ///
MEM6 BY RAB6 @ 0.582 ; ///
MEM6 BY BALLDL6 @ 0.748 ; ///
MEM6 BY FLAGDL6 @ 0.777 ; ///
MEM6 BY TREEDL6 @ 0.751 ; ///
[ RADRC6$1 @ -0.196 ] ; ///
[ RADRC6$2 @ 0.25 ] ; ///
[ RADRC6$3 @ 0.553 ] ; ///
[ RADRC6$4 @ 0.875 ] ; ///
[ RADRC6$5 @ 1.044 ] ; ///
[ RADRC6$6 @ 1.235 ] ; ///
[ RADRC6$7 @ 1.443 ] ; ///
[ RADRC6$8 @ 1.807 ] ; ///
[ RADRC6$9 @ 2.245 ] ; ///
[ RARC6$1 @ -1.702 ] ; ///
[ RARC6$2 @ -1.576 ] ; ///
[ RARC6$3 @ -1.192 ] ; ///
[ RARC6$4 @ -0.841 ] ; ///
Rev Oct 23 2015
[ RARC6$5 @ -0.5 ] ; ///
[ RARC6$6 @ -0.118 ] ; ///
[ RARC6$7 @ 0.257 ] ; ///
[ RARC6$8 @ 0.816 ] ; ///
[ RARC6$9 @ 1.203 ] ; ///
[ RA66$1 @ -0.697 ] ; ///
[ RA66$2 @ -0.062 ] ; ///
[ RA66$3 @ 0.402 ] ; ///
[ RA66$4 @ 0.732 ] ; ///
[ RA66$5 @ 0.927 ] ; ///
[ RA66$6 @ 1.087 ] ; ///
[ RA66$7 @ 1.243 ] ; ///
[ RA66$8 @ 1.688 ] ; ///
[ RA66$9 @ 2.26 ] ; ///
[ ADRG16$1 @ -1.521 ] ; ///
[ ADRG16$2 @ -1.272 ] ; ///
[ ADRG16$3 @ -1.104 ] ; ///
[ ADRG16$4 @ -0.856 ] ; ///
[ ADRG16$5 @ -0.603 ] ; ///
[ ADRG16$6 @ -0.35 ] ; ///
[ ADRG16$7 @ -0.023 ] ; ///
[ ADRG16$8 @ 0.395 ] ; ///
[ ADRG16$9 @ 0.998 ] ; ///
[ ADRG26$1 @ -1.574 ] ; ///
[ ADRG26$2 @ -1.272 ] ; ///
[ ADRG26$3 @ -1.083 ] ; ///
[ ADRG26$4 @ -0.879 ] ; ///
[ ADRG26$5 @ -0.585 ] ; ///
[ ADRG26$6 @ -0.256 ] ; ///
[ ADRG26$7 @ 0.179 ] ; ///
[ ADLT16$1 @ -1.111 ] ; ///
[ ADLT16$2 @ -0.719 ] ; ///
[ ADLT16$3 @ -0.253 ] ; ///
[ ADLT16$4 @ 0.24 ] ; ///
[ ADLT16$5 @ 0.662 ] ; ///
[ ADLT16$6 @ 1.131 ] ; ///
[ ADLT16$7 @ 1.681 ] ; ///
[ ADLT26$1 @ -1.187 ] ; ///
[ ADLT26$2 @ -0.814 ] ; ///
[ ADLT26$3 @ -0.45 ] ; ///
[ ADLT26$4 @ -0.019 ] ; ///
[ ADLT26$5 @ 0.364 ] ; ///
[ ADLT26$6 @ 0.791 ] ; ///
[ ADLT26$7 @ 1.252 ] ; ///
[ ADLT26$8 @ 1.789 ] ; ///
[ ADLT36$1 @ -1.343 ] ; ///
[ ADLT36$2 @ -0.984 ] ; ///
[ ADLT36$3 @ -0.68 ] ; ///
[ ADLT36$4 @ -0.27 ] ; ///
[ ADLT36$5 @ 0.06 ] ; ///
[ ADLT36$6 @ 0.445 ] ; ///
[ ADLT36$7 @ 0.835 ] ; ///
[ ADLT36$8 @ 1.345 ] ; ///
[ ADD6$1 @ -0.685 ] ; ///
[ ADD6$2 @ -0.399 ] ; ///
[ ADD6$3 @ -0.217 ] ; ///
[ ADD6$4 @ -0.019 ] ; ///
[ ADD6$5 @ 0.207 ] ; ///
[ ADD6$6 @ 0.355 ] ; ///
[ ADD6$7 @ 0.613 ] ; ///
[ ADD6$8 @ 0.934 ] ; ///
Rev Oct 23 2015
[ ADD6$9 @ 1.297 ] ; ///
[ RA16$1 @ -1.451 ] ; ///
[ RA16$2 @ -0.911 ] ; ///
[ RA16$3 @ -0.253 ] ; ///
[ RA16$4 @ 0.398 ] ; ///
[ RA16$5 @ 0.997 ] ; ///
[ RA16$6 @ 1.517 ] ; ///
[ RA16$7 @ 1.958 ] ; ///
[ RA26$1 @ -1.405 ] ; ///
[ RA26$2 @ -0.931 ] ; ///
[ RA26$3 @ -0.351 ] ; ///
[ RA26$4 @ 0.159 ] ; ///
[ RA26$5 @ 0.572 ] ; ///
[ RA26$6 @ 0.974 ] ; ///
[ RA26$7 @ 1.313 ] ; ///
[ RA26$8 @ 1.716 ] ; ///
[ RA26$9 @ 1.948 ] ; ///
[ RA36$1 @ -1.502 ] ; ///
[ RA36$2 @ -1.101 ] ; ///
[ RA36$3 @ -0.599 ] ; ///
[ RA36$4 @ 0.24 ] ; ///
[ RA36$5 @ 0.857 ] ; ///
[ RA36$6 @ 1.176 ] ; ///
[ RA36$7 @ 1.438 ] ; ///
[ RA36$8 @ 1.712 ] ; ///
[ RA36$9 @ 2.007 ] ; ///
[ RA46$1 @ -1.211 ] ; ///
[ RA46$2 @ -0.75 ] ; ///
[ RA46$3 @ 0.086 ] ; ///
[ RA46$4 @ 0.621 ] ; ///
[ RA46$5 @ 0.884 ] ; ///
[ RA46$6 @ 1.121 ] ; ///
[ RA46$7 @ 1.444 ] ; ///
[ RA46$8 @ 1.714 ] ; ///
[ RA46$9 @ 2.045 ] ; ///
[ RA56$1 @ -1.257 ] ; ///
[ RA56$2 @ -0.826 ] ; ///
[ RA56$3 @ -0.393 ] ; ///
[ RA56$4 @ 0.274 ] ; ///
[ RA56$5 @ 0.728 ] ; ///
[ RA56$6 @ 1.195 ] ; ///
[ RA56$7 @ 1.463 ] ; ///
[ RA56$8 @ 1.764 ] ; ///
[ RA56$9 @ 2.105 ] ; ///
[ RAB6$1 @ -1.399 ] ; ///
[ RAB6$2 @ -0.857 ] ; ///
[ RAB6$3 @ -0.164 ] ; ///
[ RAB6$4 @ 0.498 ] ; ///
[ RAB6$5 @ 1.075 ] ; ///
[ RAB6$6 @ 1.614 ] ; ///
[ RAB6$7 @ 2.052 ] ; ///
[ BALLDL6$1 @ -0.463 ] ; ///
[ FLAGDL6$1 @ -0.024 ] ; ///
[ TREEDL6$1 @ -0.139 ] ; ///
) ///
savedata(save=fscores; file=mempkc110608.dat) ///
savelog(trash)
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
Rev Oct 23 2015
sort rid
tempfile f1
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem6
sort rid
capture save "mem6", replace
******************************************************************
* 12-month
******************************************************************
use "memory_wide", clear
#d ;
local vlist lmrc12 lmd12 radrc12 rarc12 ra612 adrg112 adrg212 adlt112 adlt212 adlt312
add12 ra112 ra212 ra312 ra412 ra512 rab12 balldl12 flagdl12 treedl12;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
MEM12 BY LMRC12 @ 0.837 ; ///
MEM12 BY LMD12 @ 0.846 ; ///
MEM12 BY RADRC12 @ 0.876 ; ///
MEM12 BY RARC12 @ 0.728 ; ///
MEM12 BY RA612 @ 0.85 ; ///
MEM12 BY ADRG112 @ 0.559 ; ///
MEM12 BY ADRG212 @ 0.473 ; ///
MEM12 BY ADLT112 @ 0.765 ; ///
MEM12 BY ADLT212 @ 0.839 ; ///
MEM12 BY ADLT312 @ 0.847 ; ///
MEM12 BY ADD12 @ 0.877 ; ///
MEM12 BY RA112 @ 0.661 ; ///
MEM12 BY RA212 @ 0.807 ; ///
MEM12 BY RA312 @ 0.852 ; ///
MEM12 BY RA412 @ 0.884 ; ///
MEM12 BY RA512 @ 0.882 ; ///
MEM12 BY RAB12 @ 0.615 ; ///
MEM12 BY BALLDL12 @ 0.748 ; ///
MEM12 BY FLAGDL12 @ 0.777 ; ///
MEM12 BY TREEDL12 @ 0.751 ; ///
[ LMRC12$1 @ -1.369 ] ; ///
[ LMRC12$2 @ -0.841 ] ; ///
[ LMRC12$3 @ -0.412 ] ; ///
[ LMRC12$4 @ -0.079 ] ; ///
[ LMRC12$5 @ 0.225 ] ; ///
[ LMRC12$6 @ 0.638 ] ; ///
[ LMRC12$7 @ 0.946 ] ; ///
[ LMRC12$8 @ 1.296 ] ; ///
[ LMRC12$9 @ 1.702 ] ; ///
[ LMD12$1 @ -0.637 ] ; ///
[ LMD12$2 @ -0.289 ] ; ///
[ LMD12$3 @ 0.006 ] ; ///
[ LMD12$4 @ 0.458 ] ; ///
[ LMD12$5 @ 0.74 ] ; ///
[ LMD12$6 @ 0.854 ] ; ///
[ LMD12$7 @ 0.972 ] ; ///
[ LMD12$8 @ 1.267 ] ; ///
[ LMD12$9 @ 1.676 ] ; ///
[ RADRC12$1 @ -0.248 ] ; ///
Rev Oct 23 2015
[ RADRC12$2 @ 0.109 ] ; ///
[ RADRC12$3 @ 0.368 ] ; ///
[ RADRC12$4 @ 0.668 ] ; ///
[ RADRC12$5 @ 0.807 ] ; ///
[ RADRC12$6 @ 0.97 ] ; ///
[ RADRC12$7 @ 1.126 ] ; ///
[ RADRC12$8 @ 1.453 ] ; ///
[ RADRC12$9 @ 1.891 ] ; ///
[ RARC12$1 @ -1.624 ] ; ///
[ RARC12$2 @ -1.519 ] ; ///
[ RARC12$3 @ -1.253 ] ; ///
[ RARC12$4 @ -0.88 ] ; ///
[ RARC12$5 @ -0.543 ] ; ///
[ RARC12$6 @ -0.215 ] ; ///
[ RARC12$7 @ 0.166 ] ; ///
[ RARC12$8 @ 0.644 ] ; ///
[ RARC12$9 @ 1.053 ] ; ///
[ RA612$1 @ -0.824 ] ; ///
[ RA612$2 @ -0.242 ] ; ///
[ RA612$3 @ 0.203 ] ; ///
[ RA612$4 @ 0.526 ] ; ///
[ RA612$5 @ 0.668 ] ; ///
[ RA612$6 @ 0.859 ] ; ///
[ RA612$7 @ 1.036 ] ; ///
[ RA612$8 @ 1.424 ] ; ///
[ RA612$9 @ 1.835 ] ; ///
[ ADRG112$1 @ -1.545 ] ; ///
[ ADRG112$2 @ -1.421 ] ; ///
[ ADRG112$3 @ -1.262 ] ; ///
[ ADRG112$4 @ -1.019 ] ; ///
[ ADRG112$5 @ -0.81 ] ; ///
[ ADRG112$6 @ -0.562 ] ; ///
[ ADRG112$7 @ -0.167 ] ; ///
[ ADRG112$8 @ 0.265 ] ; ///
[ ADRG112$9 @ 0.795 ] ; ///
[ ADRG212$1 @ -1.697 ] ; ///
[ ADRG212$2 @ -1.333 ] ; ///
[ ADRG212$3 @ -1.142 ] ; ///
[ ADRG212$4 @ -0.931 ] ; ///
[ ADRG212$5 @ -0.662 ] ; ///
[ ADRG212$6 @ -0.331 ] ; ///
[ ADRG212$7 @ 0.214 ] ; ///
[ ADLT112$1 @ -1.464 ] ; ///
[ ADLT112$2 @ -0.854 ] ; ///
[ ADLT112$3 @ -0.25 ] ; ///
[ ADLT112$4 @ 0.242 ] ; ///
[ ADLT112$5 @ 0.786 ] ; ///
[ ADLT112$6 @ 1.214 ] ; ///
[ ADLT112$7 @ 1.631 ] ; ///
[ ADLT212$1 @ -1.417 ] ; ///
[ ADLT212$2 @ -1.078 ] ; ///
[ ADLT212$3 @ -0.577 ] ; ///
[ ADLT212$4 @ -0.094 ] ; ///
[ ADLT212$5 @ 0.291 ] ; ///
[ ADLT212$6 @ 0.753 ] ; ///
[ ADLT212$7 @ 1.25 ] ; ///
[ ADLT212$8 @ 1.762 ] ; ///
[ ADLT312$1 @ -1.621 ] ; ///
[ ADLT312$2 @ -1.208 ] ; ///
[ ADLT312$3 @ -0.779 ] ; ///
[ ADLT312$4 @ -0.381 ] ; ///
Rev Oct 23 2015
[ ADLT312$5 @ 0.098 ] ; ///
[ ADLT312$6 @ 0.516 ] ; ///
[ ADLT312$7 @ 0.991 ] ; ///
[ ADLT312$8 @ 1.533 ] ; ///
[ ADD12$1 @ -0.895 ] ; ///
[ ADD12$2 @ -0.521 ] ; ///
[ ADD12$3 @ -0.248 ] ; ///
[ ADD12$4 @ -0.002 ] ; ///
[ ADD12$5 @ 0.206 ] ; ///
[ ADD12$6 @ 0.408 ] ; ///
[ ADD12$7 @ 0.668 ] ; ///
[ ADD12$8 @ 0.962 ] ; ///
[ ADD12$9 @ 1.305 ] ; ///
[ RA112$1 @ -1.609 ] ; ///
[ RA112$2 @ -1.049 ] ; ///
[ RA112$3 @ -0.413 ] ; ///
[ RA112$4 @ 0.225 ] ; ///
[ RA112$5 @ 0.795 ] ; ///
[ RA112$6 @ 1.319 ] ; ///
[ RA112$7 @ 1.776 ] ; ///
[ RA212$1 @ -1.46 ] ; ///
[ RA212$2 @ -0.966 ] ; ///
[ RA212$3 @ -0.505 ] ; ///
[ RA212$4 @ -0.034 ] ; ///
[ RA212$5 @ 0.401 ] ; ///
[ RA212$6 @ 0.769 ] ; ///
[ RA212$7 @ 1.137 ] ; ///
[ RA212$8 @ 1.436 ] ; ///
[ RA212$9 @ 1.713 ] ; ///
[ RA312$1 @ -1.567 ] ; ///
[ RA312$2 @ -1.172 ] ; ///
[ RA312$3 @ -0.755 ] ; ///
[ RA312$4 @ 0.048 ] ; ///
[ RA312$5 @ 0.677 ] ; ///
[ RA312$6 @ 0.917 ] ; ///
[ RA312$7 @ 1.195 ] ; ///
[ RA312$8 @ 1.439 ] ; ///
[ RA312$9 @ 1.67 ] ; ///
[ RA412$1 @ -1.261 ] ; ///
[ RA412$2 @ -0.84 ] ; ///
[ RA412$3 @ -0.122 ] ; ///
[ RA412$4 @ 0.42 ] ; ///
[ RA412$5 @ 0.649 ] ; ///
[ RA412$6 @ 0.884 ] ; ///
[ RA412$7 @ 1.124 ] ; ///
[ RA412$8 @ 1.339 ] ; ///
[ RA412$9 @ 1.663 ] ; ///
[ RA512$1 @ -1.348 ] ; ///
[ RA512$2 @ -0.94 ] ; ///
[ RA512$3 @ -0.541 ] ; ///
[ RA512$4 @ 0.045 ] ; ///
[ RA512$5 @ 0.472 ] ; ///
[ RA512$6 @ 0.912 ] ; ///
[ RA512$7 @ 1.149 ] ; ///
[ RA512$8 @ 1.402 ] ; ///
[ RA512$9 @ 1.746 ] ; ///
[ RAB12$1 @ -1.3 ] ; ///
[ RAB12$2 @ -0.675 ] ; ///
[ RAB12$3 @ -0.063 ] ; ///
[ RAB12$4 @ 0.549 ] ; ///
[ RAB12$5 @ 1.075 ] ; ///
Rev Oct 23 2015
[ RAB12$6 @ 1.508 ] ; ///
[ RAB12$7 @ 1.868 ] ; ///
[ BALLDL12$1 @ -0.509 ] ; ///
[ FLAGDL12$1 @ -0.033 ] ; ///
[ TREEDL12$1 @ -0.127 ] ; ///
) ///
savedata(save=fscores; file=mempkc111019_12.dat) ///
savelog(trash)
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
sort rid
tempfile f1
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem12
sort rid
capture save "mem12", replace
******************************************************************
* 18 month
******************************************************************
use "memory_wide", clear
#d ;
local vlist radrc18 rarc18 ra618 adrg118 adrg218 adlt118 adlt218 adlt318 add18
ra118 ra218 ra318 ra418 ra518 rab18 balldl18 flagdl18 treedl18;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
MEM18 BY RADRC18 @ 0.885 ; ///
MEM18 BY RARC18 @ 0.716 ; ///
MEM18 BY RA618 @ 0.862 ; ///
MEM18 BY ADRG118 @ 0.43 ; ///
MEM18 BY ADRG218 @ 0.507 ; ///
MEM18 BY ADLT118 @ 0.792 ; ///
MEM18 BY ADLT218 @ 0.858 ; ///
MEM18 BY ADLT318 @ 0.844 ; ///
MEM18 BY ADD18 @ 0.898 ; ///
MEM18 BY RA118 @ 0.649 ; ///
MEM18 BY RA218 @ 0.826 ; ///
MEM18 BY RA318 @ 0.876 ; ///
MEM18 BY RA418 @ 0.884 ; ///
MEM18 BY RA518 @ 0.877 ; ///
MEM18 BY RAB18 @ 0.582 ; ///
MEM18 BY BALLDL18 @ 0.748 ; ///
MEM18 BY FLAGDL18 @ 0.777 ; ///
MEM18 BY TREEDL18 @ 0.751 ; ///
[ RADRC18$1 @ -0.196 ] ; ///
[ RADRC18$2 @ 0.25 ] ; ///
[ RADRC18$3 @ 0.553 ] ; ///
[ RADRC18$4 @ 0.875 ] ; ///
[ RADRC18$5 @ 1.044 ] ; ///
[ RADRC18$6 @ 1.235 ] ; ///
[ RADRC18$7 @ 1.443 ] ; ///
[ RADRC18$8 @ 1.807 ] ; ///
[ RADRC18$9 @ 2.245 ] ; ///
Rev Oct 23 2015
[ RARC18$1 @ -1.702 ] ; ///
[ RARC18$2 @ -1.576 ] ; ///
[ RARC18$3 @ -1.192 ] ; ///
[ RARC18$4 @ -0.841 ] ; ///
[ RARC18$5 @ -0.5 ] ; ///
[ RARC18$6 @ -0.118 ] ; ///
[ RARC18$7 @ 0.257 ] ; ///
[ RARC18$8 @ 0.816 ] ; ///
[ RARC18$9 @ 1.203 ] ; ///
[ RA618$1 @ -0.697 ] ; ///
[ RA618$2 @ -0.062 ] ; ///
[ RA618$3 @ 0.402 ] ; ///
[ RA618$4 @ 0.732 ] ; ///
[ RA618$5 @ 0.927 ] ; ///
[ RA618$6 @ 1.087 ] ; ///
[ RA618$7 @ 1.243 ] ; ///
[ RA618$8 @ 1.688 ] ; ///
[ RA618$9 @ 2.26 ] ; ///
[ ADRG118$1 @ -1.949 ] ; ///
[ ADRG118$2 @ -1.632 ] ; ///
[ ADRG118$3 @ -1.392 ] ; ///
[ ADRG118$4 @ -1.111 ] ; ///
[ ADRG118$5 @ -0.844 ] ; ///
[ ADRG118$6 @ -0.436 ] ; ///
[ ADRG118$7 @ -0.04 ] ; ///
[ ADRG118$8 @ 0.453 ] ; ///
[ ADRG118$9 @ 1.009 ] ; ///
[ ADRG218$1 @ -1.791 ] ; ///
[ ADRG218$2 @ -1.393 ] ; ///
[ ADRG218$3 @ -1.234 ] ; ///
[ ADRG218$4 @ -0.995 ] ; ///
[ ADRG218$5 @ -0.72 ] ; ///
[ ADRG218$6 @ -0.335 ] ; ///
[ ADRG218$7 @ 0.189 ] ; ///
[ ADLT118$1 @ -1.507 ] ; ///
[ ADLT118$2 @ -0.872 ] ; ///
[ ADLT118$3 @ -0.371 ] ; ///
[ ADLT118$4 @ 0.177 ] ; ///
[ ADLT118$5 @ 0.693 ] ; ///
[ ADLT118$6 @ 1.346 ] ; ///
[ ADLT118$7 @ 1.791 ] ; ///
[ ADLT218$1 @ -1.61 ] ; ///
[ ADLT218$2 @ -1.208 ] ; ///
[ ADLT218$3 @ -0.709 ] ; ///
[ ADLT218$4 @ -0.217 ] ; ///
[ ADLT218$5 @ 0.319 ] ; ///
[ ADLT218$6 @ 0.736 ] ; ///
[ ADLT218$7 @ 1.288 ] ; ///
[ ADLT218$8 @ 1.97 ] ; ///
[ ADLT318$1 @ -1.91 ] ; ///
[ ADLT318$2 @ -1.443 ] ; ///
[ ADLT318$3 @ -1.02 ] ; ///
[ ADLT318$4 @ -0.566 ] ; ///
[ ADLT318$5 @ -0.026 ] ; ///
[ ADLT318$6 @ 0.411 ] ; ///
[ ADLT318$7 @ 0.927 ] ; ///
[ ADLT318$8 @ 1.633 ] ; ///
[ ADD18$1 @ -1.147 ] ; ///
[ ADD18$2 @ -0.744 ] ; ///
[ ADD18$3 @ -0.444 ] ; ///
[ ADD18$4 @ -0.14 ] ; ///
Rev Oct 23 2015
[ ADD18$5 @ 0.115 ] ; ///
[ ADD18$6 @ 0.397 ] ; ///
[ ADD18$7 @ 0.674 ] ; ///
[ ADD18$8 @ 0.975 ] ; ///
[ ADD18$9 @ 1.461 ] ; ///
[ RA118$1 @ -1.451 ] ; ///
[ RA118$2 @ -0.911 ] ; ///
[ RA118$3 @ -0.253 ] ; ///
[ RA118$4 @ 0.398 ] ; ///
[ RA118$5 @ 0.997 ] ; ///
[ RA118$6 @ 1.517 ] ; ///
[ RA118$7 @ 1.958 ] ; ///
[ RA218$1 @ -1.405 ] ; ///
[ RA218$2 @ -0.931 ] ; ///
[ RA218$3 @ -0.351 ] ; ///
[ RA218$4 @ 0.159 ] ; ///
[ RA218$5 @ 0.572 ] ; ///
[ RA218$6 @ 0.974 ] ; ///
[ RA218$7 @ 1.313 ] ; ///
[ RA218$8 @ 1.716 ] ; ///
[ RA218$9 @ 1.948 ] ; ///
[ RA318$1 @ -1.502 ] ; ///
[ RA318$2 @ -1.101 ] ; ///
[ RA318$3 @ -0.599 ] ; ///
[ RA318$4 @ 0.24 ] ; ///
[ RA318$5 @ 0.857 ] ; ///
[ RA318$6 @ 1.176 ] ; ///
[ RA318$7 @ 1.438 ] ; ///
[ RA318$8 @ 1.712 ] ; ///
[ RA318$9 @ 2.007 ] ; ///
[ RA418$1 @ -1.211 ] ; ///
[ RA418$2 @ -0.75 ] ; ///
[ RA418$3 @ 0.086 ] ; ///
[ RA418$4 @ 0.621 ] ; ///
[ RA418$5 @ 0.884 ] ; ///
[ RA418$6 @ 1.121 ] ; ///
[ RA418$7 @ 1.444 ] ; ///
[ RA418$8 @ 1.714 ] ; ///
[ RA418$9 @ 2.045 ] ; ///
[ RA518$1 @ -1.257 ] ; ///
[ RA518$2 @ -0.826 ] ; ///
[ RA518$3 @ -0.393 ] ; ///
[ RA518$4 @ 0.274 ] ; ///
[ RA518$5 @ 0.728 ] ; ///
[ RA518$6 @ 1.195 ] ; ///
[ RA518$7 @ 1.463 ] ; ///
[ RA518$8 @ 1.764 ] ; ///
[ RA518$9 @ 2.105 ] ; ///
[ RAB18$1 @ -1.399 ] ; ///
[ RAB18$2 @ -0.857 ] ; ///
[ RAB18$3 @ -0.164 ] ; ///
[ RAB18$4 @ 0.498 ] ; ///
[ RAB18$5 @ 1.075 ] ; ///
[ RAB18$6 @ 1.614 ] ; ///
[ RAB18$7 @ 2.052 ] ; ///
[ BALLDL18$1 @ -0.632 ] ; ///
[ FLAGDL18$1 @ -0.153 ] ; ///
[ TREEDL18$1 @ -0.269 ] ; ///
) ///
savedata(save=fscores; file=mempkc111019_18.dat) ///
savelog(trash)
Rev Oct 23 2015
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
sort rid
tempfile f1
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem18
sort rid
capture save "mem18", replace
******************************************************************
* 24 month
******************************************************************
use "memory_wide", clear
#d ;
local vlist lmrc24 lmd24 radrc24 rarc24 ra624 adrg124 adrg224 adlt124 adlt224 adlt324
add24 ra124 ra224 ra324 ra424 ra524 rab24 balldl24 flagdl24 treedl24 ;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
MEM24 BY LMRC24 @ 0.837 ; ///
MEM24 BY LMD24 @ 0.846 ; ///
MEM24 BY RADRC24 @ 0.876 ; ///
MEM24 BY RARC24 @ 0.728 ; ///
MEM24 BY RA624 @ 0.85 ; ///
MEM24 BY ADRG124 @ 0.478 ; ///
MEM24 BY ADRG224 @ 0.533 ; ///
MEM24 BY ADLT124 @ 0.79 ; ///
MEM24 BY ADLT224 @ 0.828 ; ///
MEM24 BY ADLT324 @ 0.835 ; ///
MEM24 BY ADD24 @ 0.862 ; ///
MEM24 BY RA124 @ 0.661 ; ///
MEM24 BY RA224 @ 0.807 ; ///
MEM24 BY RA324 @ 0.852 ; ///
MEM24 BY RA424 @ 0.884 ; ///
MEM24 BY RA524 @ 0.882 ; ///
MEM24 BY RAB24 @ 0.615 ; ///
MEM24 BY BALLDL24 @ 0.748 ; ///
MEM24 BY FLAGDL24 @ 0.777 ; ///
MEM24 BY TREEDL24 @ 0.751 ; ///
[ LMRC24$1 @ -1.369 ] ; ///
[ LMRC24$2 @ -0.841 ] ; ///
[ LMRC24$3 @ -0.412 ] ; ///
[ LMRC24$4 @ -0.079 ] ; ///
[ LMRC24$5 @ 0.225 ] ; ///
[ LMRC24$6 @ 0.638 ] ; ///
[ LMRC24$7 @ 0.946 ] ; ///
[ LMRC24$8 @ 1.296 ] ; ///
[ LMRC24$9 @ 1.702 ] ; ///
[ LMD24$1 @ -0.637 ] ; ///
[ LMD24$2 @ -0.289 ] ; ///
[ LMD24$3 @ 0.006 ] ; ///
[ LMD24$4 @ 0.458 ] ; ///
[ LMD24$5 @ 0.74 ] ; ///
[ LMD24$6 @ 0.854 ] ; ///
[ LMD24$7 @ 0.972 ] ; ///
Rev Oct 23 2015
[ LMD24$8 @ 1.267 ] ; ///
[ LMD24$9 @ 1.676 ] ; ///
[ RADRC24$1 @ -0.248 ] ; ///
[ RADRC24$2 @ 0.109 ] ; ///
[ RADRC24$3 @ 0.368 ] ; ///
[ RADRC24$4 @ 0.668 ] ; ///
[ RADRC24$5 @ 0.807 ] ; ///
[ RADRC24$6 @ 0.97 ] ; ///
[ RADRC24$7 @ 1.126 ] ; ///
[ RADRC24$8 @ 1.453 ] ; ///
[ RADRC24$9 @ 1.891 ] ; ///
[ RARC24$1 @ -1.624 ] ; ///
[ RARC24$2 @ -1.519 ] ; ///
[ RARC24$3 @ -1.253 ] ; ///
[ RARC24$4 @ -0.88 ] ; ///
[ RARC24$5 @ -0.543 ] ; ///
[ RARC24$6 @ -0.215 ] ; ///
[ RARC24$7 @ 0.166 ] ; ///
[ RARC24$8 @ 0.644 ] ; ///
[ RARC24$9 @ 1.053 ] ; ///
[ RA624$1 @ -0.824 ] ; ///
[ RA624$2 @ -0.242 ] ; ///
[ RA624$3 @ 0.203 ] ; ///
[ RA624$4 @ 0.526 ] ; ///
[ RA624$5 @ 0.668 ] ; ///
[ RA624$6 @ 0.859 ] ; ///
[ RA624$7 @ 1.036 ] ; ///
[ RA624$8 @ 1.424 ] ; ///
[ RA624$9 @ 1.835 ] ; ///
[ ADRG124$1 @ -1.521 ] ; ///
[ ADRG124$2 @ -1.272 ] ; ///
[ ADRG124$3 @ -1.104 ] ; ///
[ ADRG124$4 @ -0.856 ] ; ///
[ ADRG124$5 @ -0.603 ] ; ///
[ ADRG124$6 @ -0.35 ] ; ///
[ ADRG124$7 @ -0.023 ] ; ///
[ ADRG124$8 @ 0.395 ] ; ///
[ ADRG124$9 @ 0.998 ] ; ///
[ ADRG224$1 @ -1.574 ] ; ///
[ ADRG224$2 @ -1.272 ] ; ///
[ ADRG224$3 @ -1.083 ] ; ///
[ ADRG224$4 @ -0.879 ] ; ///
[ ADRG224$5 @ -0.585 ] ; ///
[ ADRG224$6 @ -0.256 ] ; ///
[ ADRG224$7 @ 0.179 ] ; ///
[ ADLT124$1 @ -1.111 ] ; ///
[ ADLT124$2 @ -0.719 ] ; ///
[ ADLT124$3 @ -0.253 ] ; ///
[ ADLT124$4 @ 0.24 ] ; ///
[ ADLT124$5 @ 0.662 ] ; ///
[ ADLT124$6 @ 1.131 ] ; ///
[ ADLT124$7 @ 1.681 ] ; ///
[ ADLT224$1 @ -1.187 ] ; ///
[ ADLT224$2 @ -0.814 ] ; ///
[ ADLT224$3 @ -0.45 ] ; ///
[ ADLT224$4 @ -0.019 ] ; ///
[ ADLT224$5 @ 0.364 ] ; ///
[ ADLT224$6 @ 0.791 ] ; ///
[ ADLT224$7 @ 1.252 ] ; ///
[ ADLT224$8 @ 1.789 ] ; ///
[ ADLT324$1 @ -1.343 ] ; ///
Rev Oct 23 2015
[ ADLT324$2 @ -0.984 ] ; ///
[ ADLT324$3 @ -0.68 ] ; ///
[ ADLT324$4 @ -0.27 ] ; ///
[ ADLT324$5 @ 0.06 ] ; ///
[ ADLT324$6 @ 0.445 ] ; ///
[ ADLT324$7 @ 0.835 ] ; ///
[ ADLT324$8 @ 1.345 ] ; ///
[ ADD24$1 @ -0.685 ] ; ///
[ ADD24$2 @ -0.399 ] ; ///
[ ADD24$3 @ -0.217 ] ; ///
[ ADD24$4 @ -0.019 ] ; ///
[ ADD24$5 @ 0.207 ] ; ///
[ ADD24$6 @ 0.355 ] ; ///
[ ADD24$7 @ 0.613 ] ; ///
[ ADD24$8 @ 0.934 ] ; ///
[ ADD24$9 @ 1.297 ] ; ///
[ RA124$1 @ -1.609 ] ; ///
[ RA124$2 @ -1.049 ] ; ///
[ RA124$3 @ -0.413 ] ; ///
[ RA124$4 @ 0.225 ] ; ///
[ RA124$5 @ 0.795 ] ; ///
[ RA124$6 @ 1.319 ] ; ///
[ RA124$7 @ 1.776 ] ; ///
[ RA224$1 @ -1.46 ] ; ///
[ RA224$2 @ -0.966 ] ; ///
[ RA224$3 @ -0.505 ] ; ///
[ RA224$4 @ -0.034 ] ; ///
[ RA224$5 @ 0.401 ] ; ///
[ RA224$6 @ 0.769 ] ; ///
[ RA224$7 @ 1.137 ] ; ///
[ RA224$8 @ 1.436 ] ; ///
[ RA224$9 @ 1.713 ] ; ///
[ RA324$1 @ -1.567 ] ; ///
[ RA324$2 @ -1.172 ] ; ///
[ RA324$3 @ -0.755 ] ; ///
[ RA324$4 @ 0.048 ] ; ///
[ RA324$5 @ 0.677 ] ; ///
[ RA324$6 @ 0.917 ] ; ///
[ RA324$7 @ 1.195 ] ; ///
[ RA324$8 @ 1.439 ] ; ///
[ RA324$9 @ 1.67 ] ; ///
[ RA424$1 @ -1.261 ] ; ///
[ RA424$2 @ -0.84 ] ; ///
[ RA424$3 @ -0.122 ] ; ///
[ RA424$4 @ 0.42 ] ; ///
[ RA424$5 @ 0.649 ] ; ///
[ RA424$6 @ 0.884 ] ; ///
[ RA424$7 @ 1.124 ] ; ///
[ RA424$8 @ 1.339 ] ; ///
[ RA424$9 @ 1.663 ] ; ///
[ RA524$1 @ -1.348 ] ; ///
[ RA524$2 @ -0.94 ] ; ///
[ RA524$3 @ -0.541 ] ; ///
[ RA524$4 @ 0.045 ] ; ///
[ RA524$5 @ 0.472 ] ; ///
[ RA524$6 @ 0.912 ] ; ///
[ RA524$7 @ 1.149 ] ; ///
[ RA524$8 @ 1.402 ] ; ///
[ RA524$9 @ 1.746 ] ; ///
[ RAB24$1 @ -1.3 ] ; ///
[ RAB24$2 @ -0.675 ] ; ///
Rev Oct 23 2015
[ RAB24$3 @ -0.063 ] ; ///
[ RAB24$4 @ 0.549 ] ; ///
[ RAB24$5 @ 1.075 ] ; ///
[ RAB24$6 @ 1.508 ] ; ///
[ RAB24$7 @ 1.868 ] ; ///
[ BALLDL24$1 @ -0.509 ] ; ///
[ FLAGDL24$1 @ -0.033 ] ; ///
[ TREEDL24$1 @ -0.127 ] ; ///
) ///
savedata(save=fscores; file=mempkc111019_24.dat) ///
savelog(trash)
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
sort rid
tempfile f1
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem24
sort rid
capture save "mem24", replace
******************************************************************
* 36 month
******************************************************************
use "memory_wide", clear
#d ;
local vlist lmrc36 lmd36 radrc36 rarc36 ra636 adrg136 adrg236 adlt136 adlt236 adlt336
add36 ra136 ra236 ra336 ra436 ra536 rab36 balldl36 flagdl36 treedl36;
#d cr
runmplus rid `vlist', categorical(`vlist') id(rid) ///
model ( ///
MEM36 BY LMRC36 @ 0.837 ; ///
MEM36 BY LMD36 @ 0.846 ; ///
MEM36 BY RADRC36 @ 0.885 ; ///
MEM36 BY RARC36 @ 0.716 ; ///
MEM36 BY RA636 @ 0.862 ; ///
MEM36 BY ADRG136 @ 0.559 ; ///
MEM36 BY ADRG236 @ 0.473 ; ///
MEM36 BY ADLT136 @ 0.765 ; ///
MEM36 BY ADLT236 @ 0.839 ; ///
MEM36 BY ADLT336 @ 0.847 ; ///
MEM36 BY ADD36 @ 0.877 ; ///
MEM36 BY RA136 @ 0.649 ; ///
MEM36 BY RA236 @ 0.826 ; ///
MEM36 BY RA336 @ 0.876 ; ///
MEM36 BY RA436 @ 0.884 ; ///
MEM36 BY RA536 @ 0.877 ; ///
MEM36 BY RAB36 @ 0.582 ; ///
MEM36 BY BALLDL36 @ 0.748 ; ///
MEM36 BY FLAGDL36 @ 0.777 ; ///
MEM36 BY TREEDL36 @ 0.751 ; ///
[ LMRC36$1 @ -1.369 ] ; ///
[ LMRC36$2 @ -0.841 ] ; ///
[ LMRC36$3 @ -0.412 ] ; ///
[ LMRC36$4 @ -0.079 ] ; ///
[ LMRC36$5 @ 0.225 ] ; ///
Rev Oct 23 2015
[ LMRC36$6 @ 0.638 ] ; ///
[ LMRC36$7 @ 0.946 ] ; ///
[ LMRC36$8 @ 1.296 ] ; ///
[ LMRC36$9 @ 1.702 ] ; ///
[ LMD36$1 @ -0.637 ] ; ///
[ LMD36$2 @ -0.289 ] ; ///
[ LMD36$3 @ 0.006 ] ; ///
[ LMD36$4 @ 0.458 ] ; ///
[ LMD36$5 @ 0.74 ] ; ///
[ LMD36$6 @ 0.854 ] ; ///
[ LMD36$7 @ 0.972 ] ; ///
[ LMD36$8 @ 1.267 ] ; ///
[ LMD36$9 @ 1.676 ] ; ///
[ RADRC36$1 @ -0.196 ] ; ///
[ RADRC36$2 @ 0.25 ] ; ///
[ RADRC36$3 @ 0.553 ] ; ///
[ RADRC36$4 @ 0.875 ] ; ///
[ RADRC36$5 @ 1.044 ] ; ///
[ RADRC36$6 @ 1.235 ] ; ///
[ RADRC36$7 @ 1.443 ] ; ///
[ RADRC36$8 @ 1.807 ] ; ///
[ RADRC36$9 @ 2.245 ] ; ///
[ RARC36$1 @ -1.702 ] ; ///
[ RARC36$2 @ -1.576 ] ; ///
[ RARC36$3 @ -1.192 ] ; ///
[ RARC36$4 @ -0.841 ] ; ///
[ RARC36$5 @ -0.5 ] ; ///
[ RARC36$6 @ -0.118 ] ; ///
[ RARC36$7 @ 0.257 ] ; ///
[ RARC36$8 @ 0.816 ] ; ///
[ RARC36$9 @ 1.203 ] ; ///
[ RA636$1 @ -0.697 ] ; ///
[ RA636$2 @ -0.062 ] ; ///
[ RA636$3 @ 0.402 ] ; ///
[ RA636$4 @ 0.732 ] ; ///
[ RA636$5 @ 0.927 ] ; ///
[ RA636$6 @ 1.087 ] ; ///
[ RA636$7 @ 1.243 ] ; ///
[ RA636$8 @ 1.688 ] ; ///
[ RA636$9 @ 2.26 ] ; ///
[ ADRG136$1 @ -1.573 ] ; ///
[ ADRG136$2 @ -1.349 ] ; ///
[ ADRG136$3 @ -1.168 ] ; ///
[ ADRG136$4 @ -1.023 ] ; ///
[ ADRG136$5 @ -0.791 ] ; ///
[ ADRG136$6 @ -0.459 ] ; ///
[ ADRG136$7 @ -0.089 ] ; ///
[ ADRG136$8 @ 0.347 ] ; ///
[ ADRG136$9 @ 0.96 ] ; ///
[ ADRG236$1 @ -2.114 ] ; ///
[ ADRG236$2 @ -1.548 ] ; ///
[ ADRG236$3 @ -1.195 ] ; ///
[ ADRG236$4 @ -0.958 ] ; ///
[ ADRG236$5 @ -0.736 ] ; ///
[ ADRG236$6 @ -0.328 ] ; ///
[ ADRG236$7 @ 0.251 ] ; ///
[ ADLT136$1 @ -1.201 ] ; ///
[ ADLT136$2 @ -0.8 ] ; ///
[ ADLT136$3 @ -0.214 ] ; ///
[ ADLT136$4 @ 0.285 ] ; ///
[ ADLT136$5 @ 0.767 ] ; ///
Rev Oct 23 2015
[ ADLT136$6 @ 1.321 ] ; ///
[ ADLT136$7 @ 1.808 ] ; ///
[ ADLT236$1 @ -1.228 ] ; ///
[ ADLT236$2 @ -0.859 ] ; ///
[ ADLT236$3 @ -0.429 ] ; ///
[ ADLT236$4 @ -0.09 ] ; ///
[ ADLT236$5 @ 0.32 ] ; ///
[ ADLT236$6 @ 0.72 ] ; ///
[ ADLT236$7 @ 1.221 ] ; ///
[ ADLT236$8 @ 1.893 ] ; ///
[ ADLT336$1 @ -1.299 ] ; ///
[ ADLT336$2 @ -1.011 ] ; ///
[ ADLT336$3 @ -0.659 ] ; ///
[ ADLT336$4 @ -0.277 ] ; ///
[ ADLT336$5 @ 0.112 ] ; ///
[ ADLT336$6 @ 0.513 ] ; ///
[ ADLT336$7 @ 0.986 ] ; ///
[ ADLT336$8 @ 1.592 ] ; ///
[ ADD36$1 @ -0.704 ] ; ///
[ ADD36$2 @ -0.379 ] ; ///
[ ADD36$3 @ -0.157 ] ; ///
[ ADD36$4 @ -0.014 ] ; ///
[ ADD36$5 @ 0.145 ] ; ///
[ ADD36$6 @ 0.376 ] ; ///
[ ADD36$7 @ 0.612 ] ; ///
[ ADD36$8 @ 1.049 ] ; ///
[ ADD36$9 @ 1.499 ] ; ///
[ RA136$1 @ -1.451 ] ; ///
[ RA136$2 @ -0.911 ] ; ///
[ RA136$3 @ -0.253 ] ; ///
[ RA136$4 @ 0.398 ] ; ///
[ RA136$5 @ 0.997 ] ; ///
[ RA136$6 @ 1.517 ] ; ///
[ RA136$7 @ 1.958 ] ; ///
[ RA236$1 @ -1.405 ] ; ///
[ RA236$2 @ -0.931 ] ; ///
[ RA236$3 @ -0.351 ] ; ///
[ RA236$4 @ 0.159 ] ; ///
[ RA236$5 @ 0.572 ] ; ///
[ RA236$6 @ 0.974 ] ; ///
[ RA236$7 @ 1.313 ] ; ///
[ RA236$8 @ 1.716 ] ; ///
[ RA236$9 @ 1.948 ] ; ///
[ RA336$1 @ -1.502 ] ; ///
[ RA336$2 @ -1.101 ] ; ///
[ RA336$3 @ -0.599 ] ; ///
[ RA336$4 @ 0.24 ] ; ///
[ RA336$5 @ 0.857 ] ; ///
[ RA336$6 @ 1.176 ] ; ///
[ RA336$7 @ 1.438 ] ; ///
[ RA336$8 @ 1.712 ] ; ///
[ RA336$9 @ 2.007 ] ; ///
[ RA436$1 @ -1.211 ] ; ///
[ RA436$2 @ -0.75 ] ; ///
[ RA436$3 @ 0.086 ] ; ///
[ RA436$4 @ 0.621 ] ; ///
[ RA436$5 @ 0.884 ] ; ///
[ RA436$6 @ 1.121 ] ; ///
[ RA436$7 @ 1.444 ] ; ///
[ RA436$8 @ 1.714 ] ; ///
[ RA436$9 @ 2.045 ] ; ///
Rev Oct 23 2015
[ RA536$1 @ -1.257 ] ; ///
[ RA536$2 @ -0.826 ] ; ///
[ RA536$3 @ -0.393 ] ; ///
[ RA536$4 @ 0.274 ] ; ///
[ RA536$5 @ 0.728 ] ; ///
[ RA536$6 @ 1.195 ] ; ///
[ RA536$7 @ 1.463 ] ; ///
[ RA536$8 @ 1.764 ] ; ///
[ RA536$9 @ 2.105 ] ; ///
[ RAB36$1 @ -1.399 ] ; ///
[ RAB36$2 @ -0.857 ] ; ///
[ RAB36$3 @ -0.164 ] ; ///
[ RAB36$4 @ 0.498 ] ; ///
[ RAB36$5 @ 1.075 ] ; ///
[ RAB36$6 @ 1.614 ] ; ///
[ RAB36$7 @ 2.052 ] ; ///
[ BALLDL36$1 @ -0.408 ] ; ///
[ FLAGDL36$1 @ 0.028 ] ; ///
[ TREEDL36$1 @ -0.143 ] ; ///
) ///
savedata(save=fscores; file=mempkc111019_36.dat) ///
savelog(trash)
preserve
runmplus_load_savedata, out("trash.out") clear
keep rid mem*
sort rid
tempfile f1
save `f1'
restore
merge 1:1 rid using `f1'
keep if _merge==3
keep rid mem36
sort rid
capture save "mem36", replace
! erase ef_scores_bifactor.txt
! erase mempkc*.dat
! erase __*.dct
! erase trash.*
! erase memory_wide.dta
foreach i in 0 6 12 18 24 36 48 {
tempfile m`i'
use mem`i', clear
reshape long mem, i(rid) j(visnum)
save `m`i''
merge 1:1 rid visnum using ADNI_Mem, nogen update
save ADNI_Mem, replace
}
rename mem adni_mem
la var adni_mem "Memory summary score"
*******************************************************************************